ML Engineer (Recommendations)

📋 Description

• Design and iterate recommender systems for content, creators, and ads.
• Track and evaluate advances in recommender systems, incl. RL, bandits, seq models.
• Build and test candidate generation, ranking, and re-ranking pipelines.
• Develop experiments measuring relevance, diversity, exploration, latency, engagement.
• Collaborate with product/engineering to translate intent into modeling objectives.
• Improve feedback loops using implicit signals and sparse explicit feedback.

🎯 Requirements

• Strong ML background with recommender systems, ranking, or decision models.
• Experience with matrix factorization, embeddings, sequence models, bandits, RL.
• Ability to implement/adapt methods from recent research or OSS.
• Proficiency in PyTorch or similar; training, evaluating, deploying models.
• Comfort with large-scale behavioral data and noisy implicit feedback.
• Product intuition: link model improvements to user and business outcomes.
• Bonus: experience with large-scale recommender systems in production.
• Bonus: familiarity with exploration–exploitation tradeoffs and long-horizon optimization.

🎁 Benefits

• Join a team of ex-founders and ICML-published researchers.
• Backed by Andreessen Horowitz SR04 and top angels.
• Early-stage environment with opportunities to shape tech and culture.